Trends in Youth Labour Market Dynamics: Kenya & Rwanda (2015 - 2030)

Background

• A partnership between World Data Lab & Mastercard Foundation
• Innovatively use data to aid creation of jobs for 30M African Youth by 2030
• Informed by unprecedented youth bulge projected to rise to ~ 100M between 2023 - 2030¹
• Inability of LMICs to create high-skilled jobs that match high supply of graduates²
• And increasing skilled new entrants (~ 800K Kenya) into the job market with unmatched no. of new descent jobs
• Partnership anticipates decent jobs in Agribusiness, Green Economy, and the Digital Economy³

Employment Indicators

Figure 1: Youth emplyment-to-population ratio (EPR), Youth Not in Employment, Education or Training (NEET) and Youth Unemployment Rate (YUR).

A dive into NEET

Figure 2: Composition of Youth Population: NEET vs. Non-NEET Trends by Gender. OLF = Out of Labour Force.

NEET by gender

Figure 3: NEET trends by gender. Top panel is all the age groups, bottom panel is for the younger youth (age group 15-24).For the younger youth, gender gap is higher in Kenya indicating young women are facing barriers to enter training/job market.

Population & YUR trends by age group

Figure 4: YUR by age group. YUR higher in Rwanda. New entrants experiencing higher YUR in Kenya. YUR = Youth Unemployment Rate.

EPR by education-2

Figure 5: EPR by education. Not enough jobs for skilled workforce. Available jobs favour low skilled workers in Kenya from 2025. While skilled workers are still more employable in Rwanda, observed trend in Kenya is catching up.

Employment share by economic sector

Figure 6: A shift from agricultural subsistence activities to low productivity service activities observed for Kenya.

YUR and COVID-19 by gender

Figure 7: YUR by gender. Rwanda more hit by COVID-19 between 2020-2021 then steady recovery up to 2024.